ERI: Robotic System for Manipulation of Biological Cells and Other Microscopic Objects

In recent years, manipulation of cells and microscale objects has received significant attention due to its potential applications in biomedical and micro- and nano- technologies. Although robotic systems have made significant progress in manipulating objects at the human scale, achieving comparable dexterity at the microscopic scale remains a scientific and engineering challenge due to the distinct physical behavior and characteristics of microscopic objects. This Engineering Research Initiation (ERI) project will develop a robotic system for dexterous micromanipulation of biological cells and other microscopic objects across many types, shapes, and physical properties, thereby addressing limitations of existing micromanipulation techniques. The proposed robotic micromanipulation system will have potential applications in biomedical research, lab-on-a-chip technologies, and precision manufacturing at the microscale. In addition, the project will provide interdisciplinary research and training opportunities for high school, undergraduate, and graduate students in the laboratory, enhance curriculum with integration of research outcomes, and disseminate open-source educational modules and simulation tools for wider community benefit. The proposed robotic system consists of multiple micro-fingers that are optically actuated by laser beams. The micro-fingers are coordinated to function as a robotic hand to grasp, move, rotate, and roll cells or microscopic objects. Several fundamental theoretical challenges will be investigated to establish the foundational design principles of microscale manipulation. These include dynamic interactions between micro-fingers and target objects, coordination of micro-fingers to achieve dynamic force-closure, estimation and regulation of contact forces in the absence of practical microscale sensing, and effects of Brownian disturbances and adhesive forces. Learning algorithms will enable the system to acquire manipulation skills from expert demonstrations and repeated interactions, supporting the execution of complex manipulation tasks. Through theoretical analysis, algorithm development, and experimental validation, this research will develop a generalizable microscale robotic manipulation framework, bridging robotic manipulation across different spatial scales. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.